Overview

Brought to you by YData

Dataset statistics

Number of variables15
Number of observations30000
Missing cells74980
Missing cells (%)16.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.5 MiB
Average record size in memory1.3 KiB

Variable types

Text10
Boolean2
Categorical3

Alerts

reviews_doRecommend is highly overall correlated with reviews_rating and 1 other fieldsHigh correlation
reviews_rating is highly overall correlated with reviews_doRecommendHigh correlation
reviews_userProvince is highly overall correlated with reviews_doRecommendHigh correlation
reviews_didPurchase is highly imbalanced (56.4%) Imbalance
reviews_doRecommend is highly imbalanced (68.7%) Imbalance
reviews_didPurchase has 14068 (46.9%) missing values Missing
reviews_doRecommend has 2570 (8.6%) missing values Missing
reviews_userCity has 28071 (93.6%) missing values Missing
reviews_userProvince has 29830 (99.4%) missing values Missing

Reproduction

Analysis started2025-06-22 13:56:12.555835
Analysis finished2025-06-22 13:56:18.916311
Duration6.36 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

id
Text

Distinct271
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2025-06-22T13:56:19.187908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters600000
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)0.2%

Sample

1st rowAV13O1A8GV-KLJ3akUyj
2nd rowAV14LG0R-jtxr-f38QfS
3rd rowAV14LG0R-jtxr-f38QfS
4th rowAV16khLE-jtxr-f38VFn
5th rowAV16khLE-jtxr-f38VFn
ValueCountFrequency (%)
avpf3vofilapnd_xjpun 8545
28.5%
avpfpaoqljejml435xk9 3325
 
11.1%
avpfjp1c1cnluz0-e3xy 2039
 
6.8%
avpfw8y_ljejml437ysw 1186
 
4.0%
avpfrth1ilapnd_xyic2 1143
 
3.8%
avpf63ajljejml43f__q 873
 
2.9%
avpf0eb2ljejml43evst 845
 
2.8%
avpe41tqilapnd_xqh3d 757
 
2.5%
avpfm8yiljejml43ayyu 693
 
2.3%
avpf2tw1ilapnd_xjflc 672
 
2.2%
Other values (261) 9922
33.1%
2025-06-22T13:56:19.584629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 45592
 
7.6%
V 41098
 
6.8%
p 38641
 
6.4%
f 35966
 
6.0%
n 29274
 
4.9%
3 24175
 
4.0%
J 23350
 
3.9%
l 21320
 
3.6%
L 20965
 
3.5%
P 20151
 
3.4%
Other values (54) 299468
49.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 256949
42.8%
Uppercase Letter 236771
39.5%
Decimal Number 81829
 
13.6%
Connector Punctuation 16936
 
2.8%
Dash Punctuation 7515
 
1.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 45592
19.3%
V 41098
17.4%
J 23350
9.9%
L 20965
8.9%
P 20151
8.5%
D 15200
 
6.4%
M 10863
 
4.6%
O 10066
 
4.3%
Z 8221
 
3.5%
X 6436
 
2.7%
Other values (16) 34829
14.7%
Lowercase Letter
ValueCountFrequency (%)
p 38641
15.0%
f 35966
14.0%
n 29274
11.4%
l 21320
8.3%
i 16395
 
6.4%
u 16347
 
6.4%
e 16122
 
6.3%
x 14071
 
5.5%
c 9621
 
3.7%
j 9574
 
3.7%
Other values (16) 49618
19.3%
Decimal Number
ValueCountFrequency (%)
3 24175
29.5%
1 13080
16.0%
4 12267
15.0%
0 8106
 
9.9%
9 5819
 
7.1%
5 5656
 
6.9%
8 4038
 
4.9%
2 3382
 
4.1%
7 3378
 
4.1%
6 1928
 
2.4%
Connector Punctuation
ValueCountFrequency (%)
_ 16936
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7515
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 493720
82.3%
Common 106280
 
17.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 45592
 
9.2%
V 41098
 
8.3%
p 38641
 
7.8%
f 35966
 
7.3%
n 29274
 
5.9%
J 23350
 
4.7%
l 21320
 
4.3%
L 20965
 
4.2%
P 20151
 
4.1%
i 16395
 
3.3%
Other values (42) 200968
40.7%
Common
ValueCountFrequency (%)
3 24175
22.7%
_ 16936
15.9%
1 13080
12.3%
4 12267
11.5%
0 8106
 
7.6%
- 7515
 
7.1%
9 5819
 
5.5%
5 5656
 
5.3%
8 4038
 
3.8%
2 3382
 
3.2%
Other values (2) 5306
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 45592
 
7.6%
V 41098
 
6.8%
p 38641
 
6.4%
f 35966
 
6.0%
n 29274
 
4.9%
3 24175
 
4.0%
J 23350
 
3.9%
l 21320
 
3.6%
L 20965
 
3.5%
P 20151
 
3.4%
Other values (54) 299468
49.9%

brand
Text

Distinct214
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
2025-06-22T13:56:19.900653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length30
Median length28
Mean length9.3696667
Min length3

Characters and Unicode

Total characters281090
Distinct characters58
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)0.1%

Sample

1st rowUniversal Music
2nd rowLundberg
3rd rowLundberg
4th rowK-Y
5th rowK-Y
ValueCountFrequency (%)
clorox 10585
22.9%
home 4058
 
8.8%
warner 3994
 
8.6%
video 3993
 
8.6%
l'oreal 1310
 
2.8%
paris 1310
 
2.8%
disney 1200
 
2.6%
sony 891
 
1.9%
fox 887
 
1.9%
bees 881
 
1.9%
Other values (293) 17185
37.1%
2025-06-22T13:56:20.334313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 36010
 
12.8%
r 30031
 
10.7%
e 27968
 
9.9%
16294
 
5.8%
l 15720
 
5.6%
a 13850
 
4.9%
i 12814
 
4.6%
n 12812
 
4.6%
x 12777
 
4.5%
C 12024
 
4.3%
Other values (48) 90790
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 212319
75.5%
Uppercase Letter 48847
 
17.4%
Space Separator 16294
 
5.8%
Other Punctuation 3575
 
1.3%
Dash Punctuation 46
 
< 0.1%
Decimal Number 9
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 36010
17.0%
r 30031
14.1%
e 27968
13.2%
l 15720
7.4%
a 13850
 
6.5%
i 12814
 
6.0%
n 12812
 
6.0%
x 12777
 
6.0%
s 10754
 
5.1%
t 8147
 
3.8%
Other values (16) 31436
14.8%
Uppercase Letter
ValueCountFrequency (%)
C 12024
24.6%
H 5393
11.0%
V 4389
 
9.0%
W 4386
 
9.0%
P 2896
 
5.9%
S 2786
 
5.7%
B 2739
 
5.6%
L 2156
 
4.4%
O 1846
 
3.8%
D 1349
 
2.8%
Other values (15) 8883
18.2%
Other Punctuation
ValueCountFrequency (%)
' 2533
70.9%
. 567
 
15.9%
& 475
 
13.3%
Decimal Number
ValueCountFrequency (%)
4 6
66.7%
5 3
33.3%
Space Separator
ValueCountFrequency (%)
16294
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 261166
92.9%
Common 19924
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 36010
13.8%
r 30031
 
11.5%
e 27968
 
10.7%
l 15720
 
6.0%
a 13850
 
5.3%
i 12814
 
4.9%
n 12812
 
4.9%
x 12777
 
4.9%
C 12024
 
4.6%
s 10754
 
4.1%
Other values (41) 76406
29.3%
Common
ValueCountFrequency (%)
16294
81.8%
' 2533
 
12.7%
. 567
 
2.8%
& 475
 
2.4%
- 46
 
0.2%
4 6
 
< 0.1%
5 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 281090
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 36010
 
12.8%
r 30031
 
10.7%
e 27968
 
9.9%
16294
 
5.8%
l 15720
 
5.6%
a 13850
 
4.9%
i 12814
 
4.6%
n 12812
 
4.6%
x 12777
 
4.5%
C 12024
 
4.3%
Other values (48) 90790
32.3%

categories
Text

Distinct270
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size9.1 MiB
2025-06-22T13:56:20.532621image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length518
Median length374
Mean length262.18357
Min length42

Characters and Unicode

Total characters7865507
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)0.2%

Sample

1st rowMovies, Music & Books,Music,R&b,Movies & TV,Movie Bundles & Collections,CDs & Vinyl,Rap & Hip-Hop,Bass,Music on CD or Vinyl,Rap,Hip-Hop,Mainstream Rap,Pop Rap
2nd rowFood,Packaged Foods,Snacks,Crackers,Snacks, Cookies & Chips,Rice Cakes,Cakes
3rd rowFood,Packaged Foods,Snacks,Crackers,Snacks, Cookies & Chips,Rice Cakes,Cakes
4th rowPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,Lubricants
5th rowPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,Lubricants
ValueCountFrequency (%)
153588
 
21.5%
to 14333
 
2.0%
and 13005
 
1.8%
movies 12608
 
1.8%
tv 12200
 
1.7%
household 11321
 
1.6%
household,household 11218
 
1.6%
supplies,household 11107
 
1.6%
storage 11077
 
1.6%
brands,home 11065
 
1.5%
Other values (1885) 452408
63.4%
2025-06-22T13:56:20.869906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 721512
 
9.2%
689330
 
8.8%
s 606910
 
7.7%
o 539027
 
6.9%
a 470043
 
6.0%
, 464769
 
5.9%
i 410763
 
5.2%
n 410185
 
5.2%
l 397456
 
5.1%
r 380680
 
4.8%
Other values (61) 2774832
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5486011
69.7%
Uppercase Letter 1037009
 
13.2%
Space Separator 689330
 
8.8%
Other Punctuation 624593
 
7.9%
Dash Punctuation 20755
 
0.3%
Decimal Number 7093
 
0.1%
Open Punctuation 358
 
< 0.1%
Close Punctuation 358
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 721512
13.2%
s 606910
11.1%
o 539027
9.8%
a 470043
8.6%
i 410763
 
7.5%
n 410185
 
7.5%
l 397456
 
7.2%
r 380680
 
6.9%
t 264524
 
4.8%
u 235154
 
4.3%
Other values (16) 1049757
19.1%
Uppercase Letter
ValueCountFrequency (%)
C 187432
18.1%
S 121640
11.7%
H 102167
9.9%
B 76622
 
7.4%
M 76166
 
7.3%
P 64873
 
6.3%
F 53767
 
5.2%
T 53039
 
5.1%
A 50389
 
4.9%
W 41827
 
4.0%
Other values (14) 209087
20.2%
Decimal Number
ValueCountFrequency (%)
4 1951
27.5%
1 1015
14.3%
2 907
12.8%
3 617
 
8.7%
6 574
 
8.1%
8 496
 
7.0%
9 464
 
6.5%
5 436
 
6.1%
0 349
 
4.9%
7 284
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 464769
74.4%
& 153354
 
24.6%
' 2946
 
0.5%
# 1901
 
0.3%
/ 912
 
0.1%
. 651
 
0.1%
? 60
 
< 0.1%
Space Separator
ValueCountFrequency (%)
689330
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20755
100.0%
Open Punctuation
ValueCountFrequency (%)
( 358
100.0%
Close Punctuation
ValueCountFrequency (%)
) 358
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6523020
82.9%
Common 1342487
 
17.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 721512
 
11.1%
s 606910
 
9.3%
o 539027
 
8.3%
a 470043
 
7.2%
i 410763
 
6.3%
n 410185
 
6.3%
l 397456
 
6.1%
r 380680
 
5.8%
t 264524
 
4.1%
u 235154
 
3.6%
Other values (40) 2086766
32.0%
Common
ValueCountFrequency (%)
689330
51.3%
, 464769
34.6%
& 153354
 
11.4%
- 20755
 
1.5%
' 2946
 
0.2%
4 1951
 
0.1%
# 1901
 
0.1%
1 1015
 
0.1%
/ 912
 
0.1%
2 907
 
0.1%
Other values (11) 4647
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7865507
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 721512
 
9.2%
689330
 
8.8%
s 606910
 
7.7%
o 539027
 
6.9%
a 470043
 
6.0%
, 464769
 
5.9%
i 410763
 
5.2%
n 410185
 
5.2%
l 397456
 
5.1%
r 380680
 
4.8%
Other values (61) 2774832
35.3%

manufacturer
Text

Distinct227
Distinct (%)0.8%
Missing141
Missing (%)0.5%
Memory size1.9 MiB
2025-06-22T13:56:21.234782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length36
Median length31
Mean length9.8143608
Min length3

Characters and Unicode

Total characters293047
Distinct characters65
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)0.1%

Sample

1st rowUniversal Music Group / Cash Money
2nd rowLundberg
3rd rowLundberg
4th rowK-Y
5th rowK-Y
ValueCountFrequency (%)
clorox 8546
 
19.0%
test 3325
 
7.4%
amazonus/cloo7 2039
 
4.5%
l'oreal 1254
 
2.8%
paris 1232
 
2.7%
disney 1173
 
2.6%
walt 1172
 
2.6%
century 887
 
2.0%
fox 887
 
2.0%
bees 881
 
2.0%
Other values (343) 23491
52.3%
2025-06-22T13:56:21.736584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 29131
 
9.9%
e 22638
 
7.7%
r 21623
 
7.4%
s 15641
 
5.3%
t 15583
 
5.3%
15028
 
5.1%
C 14522
 
5.0%
l 13884
 
4.7%
n 13500
 
4.6%
a 13148
 
4.5%
Other values (55) 118349
40.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 197532
67.4%
Uppercase Letter 70456
 
24.0%
Space Separator 15028
 
5.1%
Other Punctuation 6142
 
2.1%
Decimal Number 3402
 
1.2%
Dash Punctuation 463
 
0.2%
Open Punctuation 12
 
< 0.1%
Close Punctuation 12
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 29131
14.7%
e 22638
11.5%
r 21623
10.9%
s 15641
7.9%
t 15583
7.9%
l 13884
7.0%
n 13500
6.8%
a 13148
6.7%
x 11284
 
5.7%
i 9486
 
4.8%
Other values (16) 31614
16.0%
Uppercase Letter
ValueCountFrequency (%)
C 14522
20.6%
O 6175
 
8.8%
T 5188
 
7.4%
L 5132
 
7.3%
P 4430
 
6.3%
A 3835
 
5.4%
B 3812
 
5.4%
U 3376
 
4.8%
N 2851
 
4.0%
E 2715
 
3.9%
Other values (15) 18420
26.1%
Other Punctuation
ValueCountFrequency (%)
' 2212
36.0%
/ 2170
35.3%
& 875
 
14.2%
. 483
 
7.9%
, 402
 
6.5%
Decimal Number
ValueCountFrequency (%)
7 2039
59.9%
0 671
 
19.7%
2 407
 
12.0%
1 277
 
8.1%
5 8
 
0.2%
Space Separator
ValueCountFrequency (%)
15028
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 463
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 267988
91.4%
Common 25059
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 29131
 
10.9%
e 22638
 
8.4%
r 21623
 
8.1%
s 15641
 
5.8%
t 15583
 
5.8%
C 14522
 
5.4%
l 13884
 
5.2%
n 13500
 
5.0%
a 13148
 
4.9%
x 11284
 
4.2%
Other values (41) 97034
36.2%
Common
ValueCountFrequency (%)
15028
60.0%
' 2212
 
8.8%
/ 2170
 
8.7%
7 2039
 
8.1%
& 875
 
3.5%
0 671
 
2.7%
. 483
 
1.9%
- 463
 
1.8%
2 407
 
1.6%
, 402
 
1.6%
Other values (4) 309
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 293047
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 29131
 
9.9%
e 22638
 
7.7%
r 21623
 
7.4%
s 15641
 
5.3%
t 15583
 
5.3%
15028
 
5.1%
C 14522
 
5.0%
l 13884
 
4.7%
n 13500
 
4.6%
a 13148
 
4.5%
Other values (55) 118349
40.4%

name
Text

Distinct271
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.2 MiB
2025-06-22T13:56:22.077243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length103
Median length93
Mean length53.391367
Min length13

Characters and Unicode

Total characters1601741
Distinct characters76
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)0.2%

Sample

1st rowPink Friday: Roman Reloaded Re-Up (w/dvd)
2nd rowLundberg Organic Cinnamon Toast Rice Cakes
3rd rowLundberg Organic Cinnamon Toast Rice Cakes
4th rowK-Y Love Sensuality Pleasure Gel
5th rowK-Y Love Sensuality Pleasure Gel
ValueCountFrequency (%)
clorox 10585
 
4.5%
disinfecting 10584
 
4.5%
total 8917
 
3.8%
pack 8567
 
3.7%
wipes 8561
 
3.7%
ct 8546
 
3.7%
150 8545
 
3.6%
value 8545
 
3.6%
scented 8545
 
3.6%
digital 6140
 
2.6%
Other values (1238) 146589
62.6%
2025-06-22T13:56:22.587644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
204124
 
12.7%
e 125397
 
7.8%
i 110828
 
6.9%
a 90397
 
5.6%
l 88982
 
5.6%
t 86526
 
5.4%
o 79931
 
5.0%
n 73270
 
4.6%
d 59106
 
3.7%
r 57085
 
3.6%
Other values (66) 626095
39.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1076618
67.2%
Uppercase Letter 205092
 
12.8%
Space Separator 204124
 
12.7%
Decimal Number 62409
 
3.9%
Other Punctuation 22231
 
1.4%
Dash Punctuation 10038
 
0.6%
Close Punctuation 9568
 
0.6%
Open Punctuation 9568
 
0.6%
Math Symbol 2093
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 125397
11.6%
i 110828
10.3%
a 90397
 
8.4%
l 88982
 
8.3%
t 86526
 
8.0%
o 79931
 
7.4%
n 73270
 
6.8%
d 59106
 
5.5%
r 57085
 
5.3%
s 53474
 
5.0%
Other values (16) 251622
23.4%
Uppercase Letter
ValueCountFrequency (%)
C 38945
19.0%
D 23683
11.5%
S 17760
8.7%
P 14309
 
7.0%
R 13858
 
6.8%
T 13647
 
6.7%
B 11898
 
5.8%
W 11830
 
5.8%
V 9845
 
4.8%
G 6195
 
3.0%
Other values (16) 43122
21.0%
Decimal Number
ValueCountFrequency (%)
1 13593
21.8%
5 11839
19.0%
0 10979
17.6%
3 10211
16.4%
2 9126
14.6%
6 2162
 
3.5%
4 1968
 
3.2%
7 1835
 
2.9%
8 648
 
1.0%
9 48
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/ 8266
37.2%
, 6509
29.3%
' 3187
 
14.3%
. 2174
 
9.8%
: 1446
 
6.5%
& 556
 
2.5%
! 83
 
0.4%
% 9
 
< 0.1%
" 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
204124
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10038
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9568
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9568
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2093
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1281710
80.0%
Common 320031
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 125397
 
9.8%
i 110828
 
8.6%
a 90397
 
7.1%
l 88982
 
6.9%
t 86526
 
6.8%
o 79931
 
6.2%
n 73270
 
5.7%
d 59106
 
4.6%
r 57085
 
4.5%
s 53474
 
4.2%
Other values (42) 456714
35.6%
Common
ValueCountFrequency (%)
204124
63.8%
1 13593
 
4.2%
5 11839
 
3.7%
0 10979
 
3.4%
3 10211
 
3.2%
- 10038
 
3.1%
) 9568
 
3.0%
( 9568
 
3.0%
2 9126
 
2.9%
/ 8266
 
2.6%
Other values (14) 22719
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1601741
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
204124
 
12.7%
e 125397
 
7.8%
i 110828
 
6.9%
a 90397
 
5.6%
l 88982
 
5.6%
t 86526
 
5.4%
o 79931
 
5.0%
n 73270
 
4.6%
d 59106
 
3.7%
r 57085
 
3.6%
Other values (66) 626095
39.1%

reviews_date
Text

Distinct6857
Distinct (%)22.9%
Missing46
Missing (%)0.2%
Memory size2.3 MiB
2025-06-22T13:56:22.881068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length50
Median length24
Mean length23.914669
Min length20

Characters and Unicode

Total characters716340
Distinct characters33
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4798 ?
Unique (%)16.0%

Sample

1st row2012-11-30T06:21:45.000Z
2nd row2017-07-09T00:00:00.000Z
3rd row2017-07-09T00:00:00.000Z
4th row2016-01-06T00:00:00.000Z
5th row2016-12-21T00:00:00.000Z
ValueCountFrequency (%)
2012-01-26t00:00:00.000z 1041
 
3.5%
2014-12-03t00:00:00.000z 524
 
1.7%
2014-09-19t00:00:00.000z 406
 
1.4%
2014-12-05t00:00:00.000z 345
 
1.1%
2014-12-04t00:00:00.000z 301
 
1.0%
2012-01-27t00:00:00.000z 300
 
1.0%
2014-11-07t00:00:00.000z 289
 
1.0%
2012-01-28t00:00:00.000z 278
 
0.9%
2014-12-27t00:00:00.000z 232
 
0.8%
2014-12-06t00:00:00.000z 208
 
0.7%
Other values (6854) 26086
86.9%
2025-06-22T13:56:23.293760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 313683
43.8%
1 64334
 
9.0%
- 59892
 
8.4%
: 59892
 
8.4%
2 59753
 
8.3%
Z 29946
 
4.2%
T 29946
 
4.2%
. 29263
 
4.1%
4 14752
 
2.1%
5 12918
 
1.8%
Other values (23) 41961
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 507009
70.8%
Other Punctuation 89163
 
12.4%
Dash Punctuation 59892
 
8.4%
Uppercase Letter 59892
 
8.4%
Lowercase Letter 320
 
< 0.1%
Space Separator 64
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 48
15.0%
i 48
15.0%
s 40
12.5%
e 32
10.0%
d 24
7.5%
n 24
7.5%
t 16
 
5.0%
r 16
 
5.0%
l 16
 
5.0%
h 8
 
2.5%
Other values (6) 48
15.0%
Decimal Number
ValueCountFrequency (%)
0 313683
61.9%
1 64334
 
12.7%
2 59753
 
11.8%
4 14752
 
2.9%
5 12918
 
2.5%
6 11082
 
2.2%
3 9931
 
2.0%
7 8911
 
1.8%
9 6314
 
1.2%
8 5331
 
1.1%
Other Punctuation
ValueCountFrequency (%)
: 59892
67.2%
. 29263
32.8%
" 8
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
Z 29946
50.0%
T 29946
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 59892
100.0%
Space Separator
ValueCountFrequency (%)
64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 656128
91.6%
Latin 60212
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
Z 29946
49.7%
T 29946
49.7%
o 48
 
0.1%
i 48
 
0.1%
s 40
 
0.1%
e 32
 
0.1%
d 24
 
< 0.1%
n 24
 
< 0.1%
t 16
 
< 0.1%
r 16
 
< 0.1%
Other values (8) 72
 
0.1%
Common
ValueCountFrequency (%)
0 313683
47.8%
1 64334
 
9.8%
- 59892
 
9.1%
: 59892
 
9.1%
2 59753
 
9.1%
. 29263
 
4.5%
4 14752
 
2.2%
5 12918
 
2.0%
6 11082
 
1.7%
3 9931
 
1.5%
Other values (5) 20628
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 716340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 313683
43.8%
1 64334
 
9.0%
- 59892
 
8.4%
: 59892
 
8.4%
2 59753
 
8.3%
Z 29946
 
4.2%
T 29946
 
4.2%
. 29263
 
4.1%
4 14752
 
2.1%
5 12918
 
1.8%
Other values (23) 41961
 
5.9%

reviews_didPurchase
Boolean

Imbalance  Missing 

Distinct2
Distinct (%)< 0.1%
Missing14068
Missing (%)46.9%
Memory size999.9 KiB
False
14498 
True
 
1434
(Missing)
14068 
ValueCountFrequency (%)
False 14498
48.3%
True 1434
 
4.8%
(Missing) 14068
46.9%
2025-06-22T13:56:23.382823image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

reviews_doRecommend
Boolean

High correlation  Imbalance  Missing 

Distinct2
Distinct (%)< 0.1%
Missing2570
Missing (%)8.6%
Memory size1.0 MiB
True
25880 
False
 
1550
(Missing)
 
2570
ValueCountFrequency (%)
True 25880
86.3%
False 1550
 
5.2%
(Missing) 2570
 
8.6%
2025-06-22T13:56:23.427357image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

reviews_rating
Categorical

High correlation 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.7 MiB
5
20831 
4
6020 
1
 
1384
3
 
1345
2
 
420

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters30000
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row1
5th row1

Common Values

ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%

Length

2025-06-22T13:56:23.508247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-06-22T13:56:23.584596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%

Most occurring characters

ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 30000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 20831
69.4%
4 6020
 
20.1%
1 1384
 
4.6%
3 1345
 
4.5%
2 420
 
1.4%

reviews_text
Text

Distinct27282
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size6.9 MiB
2025-06-22T13:56:23.931496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length5865
Median length1257
Mean length183.05697
Min length2

Characters and Unicode

Total characters5491709
Distinct characters94
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24711 ?
Unique (%)82.4%

Sample

1st rowi love this album. it's very good. more to the hip hop side than her current pop sound.. SO HYPE! i listen to this everyday at the gym! i give it 5star rating all the way. her metaphors are just crazy.
2nd rowGood flavor. This review was collected as part of a promotion.
3rd rowGood flavor.
4th rowI read through the reviews on here before looking in to buying one of the couples lubricants, and was ultimately disappointed that it didn't even live up to the reviews I had read. For starters, neither my boyfriend nor I could notice any sort of enhanced or 'captivating' sensation. What we did notice, however, was the messy consistency that was reminiscent of a more liquid-y vaseline. It was difficult to clean up, and was not a pleasant, especially since it lacked the 'captivating' sensation we had both been expecting. I'm disappointed that I paid as much as I did for a lube that I won't use again, when I could just use their normal personal lubricant for 1) less money and 2) less mess.
5th rowMy husband bought this gel for us. The gel caused irritation and it felt like it was burning my skin. I wouldn't recommend this gel.
ValueCountFrequency (%)
the 42938
 
4.2%
i 37866
 
3.7%
and 32804
 
3.2%
a 29963
 
2.9%
this 25934
 
2.5%
it 23211
 
2.3%
to 23140
 
2.2%
of 21078
 
2.0%
my 17191
 
1.7%
was 15854
 
1.5%
Other values (21942) 761595
73.8%
2025-06-22T13:56:24.480414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1001591
18.2%
e 507270
 
9.2%
t 372623
 
6.8%
o 352362
 
6.4%
a 328509
 
6.0%
i 290020
 
5.3%
s 284155
 
5.2%
n 250464
 
4.6%
r 240567
 
4.4%
h 200231
 
3.6%
Other values (84) 1663917
30.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4164504
75.8%
Space Separator 1001591
 
18.2%
Uppercase Letter 168357
 
3.1%
Other Punctuation 138839
 
2.5%
Decimal Number 10183
 
0.2%
Dash Punctuation 4299
 
0.1%
Close Punctuation 1925
 
< 0.1%
Open Punctuation 1626
 
< 0.1%
Math Symbol 208
 
< 0.1%
Currency Symbol 160
 
< 0.1%
Other values (2) 17
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 507270
12.2%
t 372623
 
8.9%
o 352362
 
8.5%
a 328509
 
7.9%
i 290020
 
7.0%
s 284155
 
6.8%
n 250464
 
6.0%
r 240567
 
5.8%
h 200231
 
4.8%
l 198499
 
4.8%
Other values (16) 1139804
27.4%
Uppercase Letter
ValueCountFrequency (%)
I 48641
28.9%
T 25970
15.4%
A 7839
 
4.7%
C 7608
 
4.5%
E 7568
 
4.5%
G 6880
 
4.1%
S 6022
 
3.6%
L 6006
 
3.6%
W 5911
 
3.5%
O 5508
 
3.3%
Other values (16) 40404
24.0%
Other Punctuation
ValueCountFrequency (%)
. 76645
55.2%
, 24872
 
17.9%
! 20462
 
14.7%
' 13538
 
9.8%
/ 1106
 
0.8%
: 737
 
0.5%
" 603
 
0.4%
? 390
 
0.3%
* 197
 
0.1%
& 162
 
0.1%
Other values (5) 127
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 1759
17.3%
0 1654
16.2%
2 1614
15.8%
3 1419
13.9%
5 1008
9.9%
4 926
9.1%
9 641
 
6.3%
8 461
 
4.5%
6 418
 
4.1%
7 283
 
2.8%
Math Symbol
ValueCountFrequency (%)
+ 196
94.2%
= 5
 
2.4%
> 4
 
1.9%
~ 2
 
1.0%
< 1
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 1915
99.5%
] 7
 
0.4%
} 3
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1617
99.4%
[ 8
 
0.5%
{ 1
 
0.1%
Modifier Symbol
ValueCountFrequency (%)
` 12
92.3%
^ 1
 
7.7%
Space Separator
ValueCountFrequency (%)
1001591
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4299
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 160
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4332861
78.9%
Common 1158848
 
21.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 507270
 
11.7%
t 372623
 
8.6%
o 352362
 
8.1%
a 328509
 
7.6%
i 290020
 
6.7%
s 284155
 
6.6%
n 250464
 
5.8%
r 240567
 
5.6%
h 200231
 
4.6%
l 198499
 
4.6%
Other values (42) 1308161
30.2%
Common
ValueCountFrequency (%)
1001591
86.4%
. 76645
 
6.6%
, 24872
 
2.1%
! 20462
 
1.8%
' 13538
 
1.2%
- 4299
 
0.4%
) 1915
 
0.2%
1 1759
 
0.2%
0 1654
 
0.1%
( 1617
 
0.1%
Other values (32) 10496
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5491709
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1001591
18.2%
e 507270
 
9.2%
t 372623
 
6.8%
o 352362
 
6.4%
a 328509
 
6.0%
i 290020
 
5.3%
s 284155
 
5.2%
n 250464
 
4.6%
r 240567
 
4.4%
h 200231
 
3.6%
Other values (84) 1663917
30.3%

reviews_title
Text

Distinct18535
Distinct (%)62.2%
Missing190
Missing (%)0.6%
Memory size2.1 MiB
2025-06-22T13:56:24.821352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length180
Median length104
Mean length18.096444
Min length1

Characters and Unicode

Total characters539455
Distinct characters90
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16145 ?
Unique (%)54.2%

Sample

1st rowJust Awesome
2nd rowGood
3rd rowGood
4th rowDisappointed
5th rowIrritation
ValueCountFrequency (%)
great 6103
 
6.4%
movie 3168
 
3.3%
product 3147
 
3.3%
love 2926
 
3.1%
the 2712
 
2.8%
good 2201
 
2.3%
this 1756
 
1.8%
wipes 1709
 
1.8%
for 1688
 
1.8%
clorox 1631
 
1.7%
Other values (5733) 68509
71.7%
2025-06-22T13:56:25.345663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65745
 
12.2%
e 54783
 
10.2%
o 39514
 
7.3%
t 33636
 
6.2%
r 28581
 
5.3%
i 28533
 
5.3%
a 27903
 
5.2%
s 24564
 
4.6%
n 20992
 
3.9%
l 19697
 
3.7%
Other values (80) 195507
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 400732
74.3%
Space Separator 65745
 
12.2%
Uppercase Letter 57125
 
10.6%
Other Punctuation 13859
 
2.6%
Decimal Number 1077
 
0.2%
Dash Punctuation 669
 
0.1%
Math Symbol 86
 
< 0.1%
Close Punctuation 74
 
< 0.1%
Open Punctuation 61
 
< 0.1%
Currency Symbol 25
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 54783
13.7%
o 39514
 
9.9%
t 33636
 
8.4%
r 28581
 
7.1%
i 28533
 
7.1%
a 27903
 
7.0%
s 24564
 
6.1%
n 20992
 
5.2%
l 19697
 
4.9%
d 14684
 
3.7%
Other values (16) 107845
26.9%
Uppercase Letter
ValueCountFrequency (%)
G 7429
 
13.0%
C 4434
 
7.8%
T 3873
 
6.8%
L 3681
 
6.4%
A 3625
 
6.3%
E 3481
 
6.1%
S 3110
 
5.4%
I 2861
 
5.0%
W 2688
 
4.7%
P 2614
 
4.6%
Other values (16) 19329
33.8%
Other Punctuation
ValueCountFrequency (%)
! 8506
61.4%
. 3105
 
22.4%
, 1014
 
7.3%
' 789
 
5.7%
? 102
 
0.7%
/ 89
 
0.6%
" 71
 
0.5%
& 64
 
0.5%
: 60
 
0.4%
* 32
 
0.2%
Other values (4) 27
 
0.2%
Decimal Number
ValueCountFrequency (%)
3 187
17.4%
1 183
17.0%
2 177
16.4%
0 149
13.8%
5 117
10.9%
4 89
8.3%
9 69
 
6.4%
7 42
 
3.9%
6 34
 
3.2%
8 30
 
2.8%
Math Symbol
ValueCountFrequency (%)
+ 76
88.4%
= 4
 
4.7%
~ 4
 
4.7%
| 1
 
1.2%
< 1
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 71
95.9%
] 3
 
4.1%
Open Punctuation
ValueCountFrequency (%)
( 58
95.1%
[ 3
 
4.9%
Space Separator
ValueCountFrequency (%)
65745
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 669
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 25
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 457857
84.9%
Common 81598
 
15.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 54783
 
12.0%
o 39514
 
8.6%
t 33636
 
7.3%
r 28581
 
6.2%
i 28533
 
6.2%
a 27903
 
6.1%
s 24564
 
5.4%
n 20992
 
4.6%
l 19697
 
4.3%
d 14684
 
3.2%
Other values (42) 164970
36.0%
Common
ValueCountFrequency (%)
65745
80.6%
! 8506
 
10.4%
. 3105
 
3.8%
, 1014
 
1.2%
' 789
 
1.0%
- 669
 
0.8%
3 187
 
0.2%
1 183
 
0.2%
2 177
 
0.2%
0 149
 
0.2%
Other values (28) 1074
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 539455
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
65745
 
12.2%
e 54783
 
10.2%
o 39514
 
7.3%
t 33636
 
6.2%
r 28581
 
5.3%
i 28533
 
5.3%
a 27903
 
5.2%
s 24564
 
4.6%
n 20992
 
3.9%
l 19697
 
3.7%
Other values (80) 195507
36.2%

reviews_userCity
Text

Missing 

Distinct977
Distinct (%)50.6%
Missing28071
Missing (%)93.6%
Memory size1001.0 KiB
2025-06-22T13:56:25.640577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length40
Median length22
Mean length8.6360809
Min length2

Characters and Unicode

Total characters16659
Distinct characters55
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique705 ?
Unique (%)36.5%

Sample

1st rowLos Angeles
2nd rowRohnert Park
3rd rowBrooklyn
4th rowBrooklyn
5th rowHouston
ValueCountFrequency (%)
new 51
 
2.1%
san 47
 
2.0%
city 40
 
1.7%
chicago 34
 
1.4%
houston 32
 
1.3%
york 31
 
1.3%
los 26
 
1.1%
angeles 26
 
1.1%
atlanta 23
 
1.0%
boston 22
 
0.9%
Other values (1000) 2062
86.1%
2025-06-22T13:56:26.202761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1544
 
9.3%
e 1402
 
8.4%
o 1337
 
8.0%
n 1300
 
7.8%
i 1126
 
6.8%
l 1099
 
6.6%
r 937
 
5.6%
t 894
 
5.4%
s 789
 
4.7%
465
 
2.8%
Other values (45) 5766
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13788
82.8%
Uppercase Letter 2393
 
14.4%
Space Separator 465
 
2.8%
Other Punctuation 10
 
0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1544
11.2%
e 1402
10.2%
o 1337
9.7%
n 1300
9.4%
i 1126
 
8.2%
l 1099
 
8.0%
r 937
 
6.8%
t 894
 
6.5%
s 789
 
5.7%
h 451
 
3.3%
Other values (16) 2909
21.1%
Uppercase Letter
ValueCountFrequency (%)
C 282
 
11.8%
S 226
 
9.4%
B 188
 
7.9%
L 152
 
6.4%
M 151
 
6.3%
P 138
 
5.8%
A 134
 
5.6%
W 121
 
5.1%
H 118
 
4.9%
N 117
 
4.9%
Other values (15) 766
32.0%
Other Punctuation
ValueCountFrequency (%)
. 9
90.0%
' 1
 
10.0%
Space Separator
ValueCountFrequency (%)
465
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16181
97.1%
Common 478
 
2.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1544
 
9.5%
e 1402
 
8.7%
o 1337
 
8.3%
n 1300
 
8.0%
i 1126
 
7.0%
l 1099
 
6.8%
r 937
 
5.8%
t 894
 
5.5%
s 789
 
4.9%
h 451
 
2.8%
Other values (41) 5302
32.8%
Common
ValueCountFrequency (%)
465
97.3%
. 9
 
1.9%
- 3
 
0.6%
' 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16659
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1544
 
9.3%
e 1402
 
8.4%
o 1337
 
8.0%
n 1300
 
7.8%
i 1126
 
6.8%
l 1099
 
6.6%
r 937
 
5.6%
t 894
 
5.4%
s 789
 
4.7%
465
 
2.8%
Other values (45) 5766
34.6%

reviews_userProvince
Categorical

High correlation  Missing 

Distinct42
Distinct (%)24.7%
Missing29830
Missing (%)99.4%
Memory size1.8 MiB
CA
19 
TX
16 
FL
15 
OH
15 
NJ
10 
Other values (37)
95 

Length

Max length10
Median length2
Mean length2.0941176
Min length2

Characters and Unicode

Total characters356
Distinct characters36
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)8.2%

Sample

1st rowMI
2nd rowTX
3rd rowTX
4th rowME
5th rowOH

Common Values

ValueCountFrequency (%)
CA 19
 
0.1%
TX 16
 
0.1%
FL 15
 
0.1%
OH 15
 
0.1%
NJ 10
 
< 0.1%
MI 8
 
< 0.1%
NY 5
 
< 0.1%
IN 5
 
< 0.1%
AZ 5
 
< 0.1%
GA 4
 
< 0.1%
Other values (32) 68
 
0.2%
(Missing) 29830
99.4%

Length

2025-06-22T13:56:26.388354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ca 19
 
11.2%
tx 16
 
9.4%
fl 15
 
8.8%
oh 15
 
8.8%
nj 10
 
5.9%
mi 8
 
4.7%
ny 5
 
2.9%
in 5
 
2.9%
az 5
 
2.9%
ga 4
 
2.4%
Other values (32) 68
40.0%

Most occurring characters

ValueCountFrequency (%)
A 49
13.8%
N 33
 
9.3%
C 28
 
7.9%
L 25
 
7.0%
I 24
 
6.7%
O 24
 
6.7%
T 23
 
6.5%
M 20
 
5.6%
H 18
 
5.1%
X 16
 
4.5%
Other values (26) 96
27.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 337
94.7%
Lowercase Letter 19
 
5.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 49
14.5%
N 33
9.8%
C 28
 
8.3%
L 25
 
7.4%
I 24
 
7.1%
O 24
 
7.1%
T 23
 
6.8%
M 20
 
5.9%
H 18
 
5.3%
X 16
 
4.7%
Other values (14) 77
22.8%
Lowercase Letter
ValueCountFrequency (%)
a 4
21.1%
m 3
15.8%
n 2
10.5%
i 2
10.5%
e 1
 
5.3%
g 1
 
5.3%
d 1
 
5.3%
r 1
 
5.3%
f 1
 
5.3%
u 1
 
5.3%
Other values (2) 2
10.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 356
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 49
13.8%
N 33
 
9.3%
C 28
 
7.9%
L 25
 
7.0%
I 24
 
6.7%
O 24
 
6.7%
T 23
 
6.5%
M 20
 
5.6%
H 18
 
5.1%
X 16
 
4.5%
Other values (26) 96
27.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 356
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 49
13.8%
N 33
 
9.3%
C 28
 
7.9%
L 25
 
7.0%
I 24
 
6.7%
O 24
 
6.7%
T 23
 
6.5%
M 20
 
5.6%
H 18
 
5.1%
X 16
 
4.5%
Other values (26) 96
27.0%

reviews_username
Text

Distinct24914
Distinct (%)83.2%
Missing63
Missing (%)0.2%
Memory size1.9 MiB
2025-06-22T13:56:26.937214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length59
Median length34
Mean length8.0268898
Min length1

Characters and Unicode

Total characters240301
Distinct characters49
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21304 ?
Unique (%)71.2%

Sample

1st rowjoshua
2nd rowdorothy w
3rd rowdorothy w
4th rowrebecca
5th rowwalker557
ValueCountFrequency (%)
the 62
 
0.2%
customer 56
 
0.2%
mike 43
 
0.1%
byamazon 43
 
0.1%
chris 33
 
0.1%
m 26
 
0.1%
b 23
 
0.1%
a 20
 
0.1%
d 20
 
0.1%
lisa 20
 
0.1%
Other values (25015) 30803
98.9%
2025-06-22T13:56:27.748020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 21155
 
8.8%
e 21024
 
8.7%
i 13809
 
5.7%
r 13783
 
5.7%
n 13493
 
5.6%
o 12621
 
5.3%
s 12192
 
5.1%
l 11852
 
4.9%
m 10973
 
4.6%
t 9900
 
4.1%
Other values (39) 99499
41.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 210254
87.5%
Decimal Number 28567
 
11.9%
Space Separator 1212
 
0.5%
Other Punctuation 193
 
0.1%
Connector Punctuation 41
 
< 0.1%
Dash Punctuation 26
 
< 0.1%
Math Symbol 4
 
< 0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 21155
 
10.1%
e 21024
 
10.0%
i 13809
 
6.6%
r 13783
 
6.6%
n 13493
 
6.4%
o 12621
 
6.0%
s 12192
 
5.8%
l 11852
 
5.6%
m 10973
 
5.2%
t 9900
 
4.7%
Other values (16) 69452
33.0%
Decimal Number
ValueCountFrequency (%)
1 5290
18.5%
2 4381
15.3%
0 3135
11.0%
3 2724
9.5%
7 2381
8.3%
4 2296
8.0%
8 2234
7.8%
9 2204
7.7%
5 2151
7.5%
6 1771
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 171
88.6%
' 7
 
3.6%
! 6
 
3.1%
, 5
 
2.6%
* 1
 
0.5%
& 1
 
0.5%
: 1
 
0.5%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
1212
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 210258
87.5%
Common 30043
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 21155
 
10.1%
e 21024
 
10.0%
i 13809
 
6.6%
r 13783
 
6.6%
n 13493
 
6.4%
o 12621
 
6.0%
s 12192
 
5.8%
l 11852
 
5.6%
m 10973
 
5.2%
t 9900
 
4.7%
Other values (17) 69456
33.0%
Common
ValueCountFrequency (%)
1 5290
17.6%
2 4381
14.6%
0 3135
10.4%
3 2724
9.1%
7 2381
7.9%
4 2296
7.6%
8 2234
7.4%
9 2204
7.3%
5 2151
7.2%
6 1771
 
5.9%
Other values (12) 1476
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 240301
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 21155
 
8.8%
e 21024
 
8.7%
i 13809
 
5.7%
r 13783
 
5.7%
n 13493
 
5.6%
o 12621
 
5.3%
s 12192
 
5.1%
l 11852
 
4.9%
m 10973
 
4.6%
t 9900
 
4.1%
Other values (39) 99499
41.4%

user_sentiment
Categorical

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size1.9 MiB
Positive
26632 
Negative
3367 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters239992
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPositive
2nd rowPositive
3rd rowPositive
4th rowNegative
5th rowNegative

Common Values

ValueCountFrequency (%)
Positive 26632
88.8%
Negative 3367
 
11.2%
(Missing) 1
 
< 0.1%

Length

2025-06-22T13:56:27.919425image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-06-22T13:56:28.008474image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
positive 26632
88.8%
negative 3367
 
11.2%

Most occurring characters

ValueCountFrequency (%)
i 56631
23.6%
e 33366
13.9%
v 29999
12.5%
t 29999
12.5%
o 26632
11.1%
P 26632
11.1%
s 26632
11.1%
N 3367
 
1.4%
g 3367
 
1.4%
a 3367
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 209993
87.5%
Uppercase Letter 29999
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 56631
27.0%
e 33366
15.9%
v 29999
14.3%
t 29999
14.3%
o 26632
12.7%
s 26632
12.7%
g 3367
 
1.6%
a 3367
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
P 26632
88.8%
N 3367
 
11.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 239992
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 56631
23.6%
e 33366
13.9%
v 29999
12.5%
t 29999
12.5%
o 26632
11.1%
P 26632
11.1%
s 26632
11.1%
N 3367
 
1.4%
g 3367
 
1.4%
a 3367
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 239992
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 56631
23.6%
e 33366
13.9%
v 29999
12.5%
t 29999
12.5%
o 26632
11.1%
P 26632
11.1%
s 26632
11.1%
N 3367
 
1.4%
g 3367
 
1.4%
a 3367
 
1.4%

Correlations

2025-06-22T13:56:28.523864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
reviews_didPurchasereviews_doRecommendreviews_ratingreviews_userProvinceuser_sentiment
reviews_didPurchase1.0000.0000.0540.0000.043
reviews_doRecommend0.0001.0000.8340.8060.199
reviews_rating0.0540.8341.0000.1230.244
reviews_userProvince0.0000.8060.1231.0000.000
user_sentiment0.0430.1990.2440.0001.000

Missing values

2025-06-22T13:56:18.251385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-06-22T13:56:18.452138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-06-22T13:56:18.710818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idbrandcategoriesmanufacturernamereviews_datereviews_didPurchasereviews_doRecommendreviews_ratingreviews_textreviews_titlereviews_userCityreviews_userProvincereviews_usernameuser_sentiment
0AV13O1A8GV-KLJ3akUyjUniversal MusicMovies, Music & Books,Music,R&b,Movies & TV,Movie Bundles & Collections,CDs & Vinyl,Rap & Hip-Hop,Bass,Music on CD or Vinyl,Rap,Hip-Hop,Mainstream Rap,Pop RapUniversal Music Group / Cash MoneyPink Friday: Roman Reloaded Re-Up (w/dvd)2012-11-30T06:21:45.000ZNaNNaN5i love this album. it's very good. more to the hip hop side than her current pop sound.. SO HYPE! i listen to this everyday at the gym! i give it 5star rating all the way. her metaphors are just crazy.Just AwesomeLos AngelesNaNjoshuaPositive
1AV14LG0R-jtxr-f38QfSLundbergFood,Packaged Foods,Snacks,Crackers,Snacks, Cookies & Chips,Rice Cakes,CakesLundbergLundberg Organic Cinnamon Toast Rice Cakes2017-07-09T00:00:00.000ZTrueNaN5Good flavor. This review was collected as part of a promotion.GoodNaNNaNdorothy wPositive
2AV14LG0R-jtxr-f38QfSLundbergFood,Packaged Foods,Snacks,Crackers,Snacks, Cookies & Chips,Rice Cakes,CakesLundbergLundberg Organic Cinnamon Toast Rice Cakes2017-07-09T00:00:00.000ZTrueNaN5Good flavor.GoodNaNNaNdorothy wPositive
3AV16khLE-jtxr-f38VFnK-YPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,LubricantsK-YK-Y Love Sensuality Pleasure Gel2016-01-06T00:00:00.000ZFalseFalse1I read through the reviews on here before looking in to buying one of the couples lubricants, and was ultimately disappointed that it didn't even live up to the reviews I had read. For starters, neither my boyfriend nor I could notice any sort of enhanced or 'captivating' sensation. What we did notice, however, was the messy consistency that was reminiscent of a more liquid-y vaseline. It was difficult to clean up, and was not a pleasant, especially since it lacked the 'captivating' sensation we had both been expecting. I'm disappointed that I paid as much as I did for a lube that I won't use again, when I could just use their normal personal lubricant for 1) less money and 2) less mess.DisappointedNaNNaNrebeccaNegative
4AV16khLE-jtxr-f38VFnK-YPersonal Care,Medicine Cabinet,Lubricant/Spermicide,Health,Sexual Wellness,LubricantsK-YK-Y Love Sensuality Pleasure Gel2016-12-21T00:00:00.000ZFalseFalse1My husband bought this gel for us. The gel caused irritation and it felt like it was burning my skin. I wouldn't recommend this gel.IrritationNaNNaNwalker557Negative
idbrandcategoriesmanufacturernamereviews_datereviews_didPurchasereviews_doRecommendreviews_ratingreviews_textreviews_titlereviews_userCityreviews_userProvincereviews_usernameuser_sentiment
29990AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2016-12-26T00:00:00.000ZFalseTrue5This whole set of these (mask, shampoo and conditioner) works lovely. My roots get oily quickly and with this, they didn't! The smells of the mask and shampoo are alright, but I think the conditioner smells AMAZING. Recommend for anyone with the same oily root/dry ends problem. *I had received these products free/complimentary for testing purposes. All opinions are my own.* This review was collected as part of a promotion.Smells Amazing!NaNNaNemily646Positive
29991AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-07T00:00:00.000ZFalseTrue5Took the 48 hour hair challenge using the shampoo, conditioner and clay mask. this was the 1st time I've heard of using clay. It worked good. My hair was clean. It smells good. It lasted 48 hours without getting oily. Received these products free for testing purposes but all opinions are my own. This review was collected as part of a promotion.Great clay products!NaNNaNmeganjoywolfePositive
29992AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2016-12-16T00:00:00.000ZFalseTrue5I absolutely love the smell of this product! I have fine hair that is oily at the roots but the ends are dry. This left my hair feeling soft, the ends are not dry, and I didn't have to wash my hair last night (which I have to usually wash my hair every night). I couldn't be happier with this product and will most definitely be purchasing it again. I received these products free/complimentary for testing purposes, but all opinions are your own. This review was collected as part of a promotion.Smells AmazingNaNNaNkjb2205Positive
29993AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-23T00:00:00.000ZFalseTrue5I seriously was so surprised after my shower how soft and healthy my shaft and ends felt and looked! not to mention super soft!! i received this product free for my review. This review was collected as part of a promotion.Ends feel so soft!NaNNaNmaryyyyyalicePositive
29994AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-14T00:00:00.000ZFalseTrue5I got to try this conditioner for free and boy am I glad I did! It's amazing. It leaves your hair so soft and manageable and smells even more amazing! I would recommend anyone who wants great feeling hair that's not oily or dry to give this a try, you won't be disappointed. This review was collected as part of a promotion.By far, my new favorite conditionerNaNNaNsmartthunnyPositive
29995AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-23T00:00:00.000ZFalseTrue5I got this conditioner with Influenster to try it and im loving it so far, i have oily hair so i use it only in the ends of my hair and feels amazing, so soft and no mess!! This review was collected as part of a promotion.Softness!!NaNNaNlaurasnchzPositive
29996AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-27T00:00:00.000ZFalseTrue5I love it , I received this for review purposes from influenster and it leaves my hair feeling fresh and smelling greatI love itNaNNaNscarlepadillaPositive
29997AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-21T00:00:00.000ZFalseTrue5First of all I love the smell of this product. After you wash your hair it is so smooth and easy to brush! I did receive this product from influenster for testing purposes but all opinions ARE my own! This review was collected as part of a promotion.Hair is so smooth after useNaNNaNliviasuexoPositive
29998AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-11T00:00:00.000ZFalseTrue5I received this through Influenster and will never go back to anything else! I normally don't use conditioner because my hair is so oily and fine. This does not make my hair feel heavy, and it doesn't get oily during the day! It really is fantastic and plan on buying it in the future! This review was collected as part of a promotion.Perfect for my oily hair!NaNNaNktreed95Positive
29999AVpfW8y_LJeJML437ySWL'oreal ParisBeauty,Hair Care,Shampoo & Conditioner,Holiday Shop,Christmas,Featured Brands,Health & Beauty,L'oreal,Personal Care,Hair Treatments,ConditionerL'oreal ParisL'or233al Paris Elvive Extraordinary Clay Rebalancing Conditioner - 12.6 Fl Oz2017-01-19T00:00:00.000ZFalseTrue5I received this product complimentary from influenster and it has really saved my hair. This product really gives the extra boost of health and strength to bring hair back to life. It hasn't helped my hair in so many ways. This review was collected as part of a promotion.Conditioned into healthyNaNNaNkcoopxoxoPositive